The rapid rise of artificial intelligence is no longer just a question of software, productivity, or automation. It is beginning to influence how some of the most influential figures in technology think about human development itself. In a recent podcast interview, Alexandr Wang, one of the most prominent AI leaders working closely with Meta, shared a striking personal view about parenthood, childhood learning, and brain computer interfaces.
Wang explained that he would prefer to wait before having children until technologies like Neuralink are far more advanced, stable, and widely accessible. His reasoning is rooted in neuroscience, but it also reflects a broader concern about the future relationship between humans and artificial intelligence.
Why Early Childhood Brain Development Matters
Neuroscience research consistently shows that the human brain is most adaptable during early childhood. Roughly speaking, the first seven years of life represent a period of exceptional neural plasticity, when the brain forms connections at a speed that is never matched again later in life.
Wang’s argument builds on this idea. He suggests that children growing up with brain computer interfaces could learn to interact with these systems in a more natural and intuitive way than adults ever could. Rather than adapting to technology after decades of purely biological learning, children might integrate digital interfaces directly into their cognitive development.
This is not about faster typing or improved memory alone. It points to a deeper form of learning, where interaction with machines becomes part of how the brain itself organizes information, problem solving, and creativity.
Neuralink and the Promise of Brain Computer Interfaces
Brain computer interfaces, often referred to as BCI, aim to create a direct communication pathway between the brain and external systems. Neuralink, founded by Elon Musk, is one of the most visible companies working on this technology, although it is far from alone in the field.
Wang emphasizes that he is not interested in early adoption for its own sake. His position is cautious. He says he would only consider this future once such systems are proven to be safe, reliable, and accessible beyond a small experimental group.
The embedded video in this article shows Wang explaining his reasoning in his own words, providing essential nuance that headlines alone often miss. His tone is reflective rather than promotional, and he repeatedly stresses uncertainty rather than inevitability.
Children, AI, and Cognitive Enhancement
At the heart of Wang’s perspective lies a concern shared by many AI researchers. Artificial intelligence is progressing at an exponential pace, while human biological evolution moves slowly. This widening gap raises uncomfortable questions about long-term competitiveness and relevance.
From this viewpoint, cognitive enhancement is not framed as a luxury or transhuman fantasy. It is described as a possible adaptation mechanism. Direct neural links to AI systems could one day allow humans to process information, reason, or collaborate with machines in ways that keep pace with increasingly powerful models.
For children born into such a world, these tools would not feel like enhancements added later in life. They would simply be part of how thinking works.
Ethical and Social Questions Still Unanswered
Wang’s comments also highlight how many questions remain unresolved. Who would control access to these technologies? How would safety be ensured for developing brains? Would cognitive enhancement deepen existing inequalities between those who can afford it and those who cannot?
There is also the issue of choice. A child cannot meaningfully consent to permanent neurological changes. Any future involving early brain computer interfaces would require new ethical frameworks, far beyond current debates around screen time or data privacy.
Importantly, Wang does not claim to have answers. His remarks reflect uncertainty and caution as much as optimism.
A Signal From the AI Industry
When someone in Wang’s position speaks openly about delaying parenthood until technology catches up with his expectations, it sends a signal. It suggests that parts of the AI industry are thinking far beyond short-term applications and quarterly results.
Whether or not brain computer interfaces become mainstream, the underlying concern remains relevant. Artificial intelligence is reshaping the environment in which future generations will learn, think, and compete. Wang’s perspective invites a broader discussion about how society prepares for that reality, not just technologically, but ethically and culturally as well.
As AI systems continue to evolve, the question may no longer be whether humans adapt to machines, but how early that adaptation begins.